>3/18 24: Similarities between Electronic Computers and the Human Brain: Thank you Jensen Huang for best week of Learning since John Von Neumann shared with The Economist 1956 notes Computer & The Brain
HAPPY 2024: in this 74th year since The Economist started mediating futures of brainworking machines clued by the 3 maths greats NET (Neumann, Einstein, Turing) people seem to be chatting about 5 wholly different sorts of AI. 1BAD: The worst tech system designers don't deserve inclusion in human intel at all, and as Hoover's Condoleezza Rice . 2 reports their work is result of 10 compound techs of which Ai is but one. Those worst for world system designs may use media to lie or multiply hate or hack, and to perpetuate tribal wars and increase trade in arms. Sadly bad versions of tv media began in USA early 1960s when it turned out what had been the nation's first major export crop, tobacco, was a killer. Please note for a long time farmers did not know bac was bad: western HIStory is full of ignorances which lawyer-dominated societies then cover up once inconvenient system truths are seen. A second AI ecommerce type (now 25 years exponential development strong) ; this involves ever more powerful algorithms applied to a company's data platform that can be app'd to hollow out community making relatively few people richer and richer, or the reverse. You can test a nation's use of this ai by seeing if efinance has invested in the poorest or historically most disconnected - see eg bangladesh's bklash, one of the most populous digital cash systems . Digital money is far cheaper to distribute let alone to manually account for so power AI offers lots of lessons but whether its good or not depends in part on whether there are enough engineers in gov & public service to see ahead of what needs regulating. There are 2 very good ai's which have only scaled in recent years that certainly dont need regulating by non engineers and one curious ai which was presented to congress in 2018 but which was left to multiply at least 100 variants today the so-called chats or LLMs. Lets look at the 2 very good ai's first because frankly if your community is concerned about any extinction risks these AI may most likely save you, One I call science AI and frankly in the west one team is so far ahead that we should count ourselves lucky that its originator Hassabis has mixed wealth and societal growth. His deep mind merged with google to make wealth but open sourced the 200 million protein databank equivalent to a billion hours of doctorate time- so now's the time for biotech to save humanity if it ever does. Alongside this the second very good AI graviates around Fei-Fei Li) in developing 20 million imagenet database so that annual competitions training computers to see 20000 of the most everyday sights we humans view around the world including things and life-forms such as nature's plants and animals. Today, students no longer need to go back to 0.1 programming to ask computer about any of these objects; nor do robots or and autonomous vehicles - see fei-fei li's book worlds i see which is published in melinda gates Entrepreneurial Revolution of girl empowerment
EW::ED , VN Hypothesis: in 21st C brainworking worlds how people's times & data are spent is foundational to place's community health, energy and so natural capacity to grow/destroy wealth -thus species will depend on whether 1000 mother tongue language model mediates intelligence/maths so all communities cooperatively celebrate lifetimes and diversity's deep data ) . Check out "Moore exponential patterns" at year 73 of celebrating Game : Architect Intelligence (Ai) - players welcome .. some jargon

Saturday, December 31, 2022

May I wish everyone a happy, safe & Virus Ending New Year - in cooperation search of HAI Human-centred Art Intel

F1 When I lightly sprained my ankle avoiding a wheelchair traveling at 10 mph down the narrow corridors of Cambridge maths lab in 1972, I didn't recognise my close encounter. In fact I spent the rest of my time at DAMTP trying to stay out of Steve Hawkins' way. With hindsight I learnt 2 things about myself. I am not a a mathematical wizard. But wherever I am lucky enough to friends someone who has met a wizard I try to prepare a deeper question every time I get a chance to discuss that wizard. Continued in foot 1

Contextual Grounded Mapping of Maths and Relationship Systems.

aka journeying through every GPS around human and female centric intel, economics and coms


Q1 what are relationship systems of 1 nature, 2 human design? my preferred answer - systems are maps of relationship connections that involve exponential governance : their consequence is either a rising or collapsing exponential -chekour jargon spinning virtuous or vicious (or double loop reinforcement mapping) 

Q2 what does exponential valuation of living systems integrate? i focus on two observable patterns of integration- nature's and man-made. There are moments in the future history of humanit when nature requires us to unite around a higher order understanding than previously known. For example Darwin provided enough evidence that nature as a life-giving or life-taking power offers in some ways ahead that are even more fundamental than the golden rule religions codes of what thu  shalt ir shall not do to one another. 

Q3 do economiics and intelligence result in equivalent futures of life? It is my hypothesis that they do because both define or are defined by what system mapping maths does. Whilst not a great fan of 2 dimensional frameworks may I suggest that we consider:

natural versus man made - exercise how do you interpret viral in nature's context and in the messaging contect of anti-coial or social media/mediation 

logical/ethical heuristics versus deep data analysis : exercise around 1970 did logical economics get increasingly replaecd by number crucnhing economents; around 2006 did heurisdtics models of intelligence get replaced by deep data learning modles

Q4 Now Valuetrue question on which uniting 8 billion human's advancement on degradation depends - to what extent have data analyses of economics and intelligence demonstrated completely different visons? Until economsits and brainworkers talk the same code:  If you are parent, which vision's exponential consequences do you back for your children's lives of relationships to be harmoniously empowered by nature's?

HISTORY CLUES - we knew when the UN was born that Computer brainpower would infinitely exceed humans alone by the time millennials grew up. So the only true question was how to make sure the maths of data zooming up and dw from every gps improved human and intel relationships emotional celebration of each other. 

1951 was both the year I was born and the year The Economist seconded my father (Norman) had survived spending his last day as teen navigating airplanes allied bomber command Burma giving him google maps of coastlines in his head 50 years before any other mediator) to New York Princeton where Von Neumann's brain was multiplying probably the greatest wonders one brain with no more than a slideruler has ever visioned in a 7 year period ( HAI hopes to see much "moore" good interacted) 

What had happened 1945-1951 was the the first 7 year action learning curve of Uniting Nations; and the last when TEN could all be interviewed - t DIED IN 54, e DIED IN 55, n DIED IN 57.

. In terms of multiplying human intelligence this grunded extraordinary ops for brainworking if you wanted to web  NYP North to Boston MIT via eg IBM and yale; 

or NYP south by sw to nulear disarmament and space (or so the MAI (male AI) cooperation network of Turing Eiintein Neumann desperately sought to be their legacy). Recall 1945-1865: The first 80 years of spinning every more communiactiosn across the world had Switzerland ITU as its epicentre - a place where people tried to stay neutral to 2 (or today 3)  world wars rooted in N-S land-locked nations above the old world's landbridge to 3 continents made more comlex when it was both canalled and found to be the wests treasure map to oil. Itwas therefore hugely important that UNP trianguarised its 2 coastal human co-creatity corridors with its digital twin (the ITU was co-branded tech for good UN out of the  old league of nations Switzerland had also mediated with exciting neibors like the Red Cross which made Geneva the UN headquarters of Who's Health Who).

There in Princeton 1951 Von Neuman asked father whether the vision of economists and Neumann's peers including Einstein and Turing was congruent. The editor Geoffrey Crowther who had just completed the cenetanry autobiography of The Economist 1943-1843 said yes provided that we continue to search the 2 questions that united founder of Economist james Wilson and Queen Victoria

How do humans generate life times and demand quality of leadership so that we are relentlessly mapping how to end poverty and end hunger

If you have got this far I would hope that you have more questions than answers. I am happy to try and respknd to any question worth of your and my time. Or have a look around this blog - we try and explore life's lessons of both some of the greats of maths and of the greatest of communally serving each other.

 Foot 1:I have sent a large part of my life on mapping media consequences through behavioral surveys of both subconscious and concsious human energies. Grounded theory is a conveneiently simpy way to contextually focusd deeper and deeper conversational understand. I would recommend any 5th grade teacher knows how to do it. Beware its as least as simple as anthing else we educate pre-teens on but it will unleash a curiosity which is opposite to that of wanting to being examined on 100% correct theories. 

F2 Being born 1951 in London was a strange time to get ed in maths. At school our greatest ABT (analytic brain tool) was a slide ruler; I first met a computer during my gap year at Miniistry of Transport (my job carring binary decs cards to government's mainframe at the central electricity generating board ; while i did a bit of fortan at university, the electric calculatr was our main abt; then my first job 1973 let us loose on dec pdp mini comps at the national development project of computer assisted learning - there we developed conversational stats learning across 2000 students at 4 univerities asyncronously - we were visited by american at plat and told were ding the opposite of expert systems - i thought this was good but we soon got defunded by bureaucrats and i left to see if computers could assist with national opinion polling ...)

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